About the job
We are building the next generation of autonomous AI agents that enable Amazon customers to seamlessly discover and purchase products across the open web. Our systems operate in highly dynamic real-world environments, navigating thousands of third-party merchant experiences with production-grade reliability, scalability, and safety. This role sits at the intersection of Agentic AI, LLMs, reinforcement learning, multimodal reasoning, and large-scale distributed systems. As an Applied Scientist, you will help define the science and architecture powering internet-scale web agents and autonomous purchasing systems.
Responsibilities
- Work on autonomous AI agents operating in open-world environments rather than static benchmarks.
- Solve challenging research problems at the intersection of LLMs, web interaction, multimodal reasoning, and scalable systems.
- Influence products that directly impact millions of Amazon customers.
- Build systems that must generalize across thousands of constantly evolving third-party websites.
- Partner closely with science, engineering, and product leaders to shape the future of AI-powered shopping experiences.
- Have the opportunity to publish research, file patents, and contribute to Amazon-wide AI innovation.
Qualifications
Minimum
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
Preferred
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.